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Machine learning for scientific discovery: how far can data-driven approaches take us?
Sala S-006-0Palestrante: Emille E. O. Ishida, pesquisadora do CNRS, França The significant increase in volume and complexity of data resulting from technological development is a common challenge faced by many scientific disciplines. More sensitive detectors and large scale experiments are currently overwhelming researchers who were obliged to turn to automatic machine learning algorithms in order to […]